The female labor force participation (FLFP) rate is a critical indicator of a nation's socioeconomic development. High FLFP is associated with women's empowerment, improved social and economic outcomes, and enhanced utilization of human potential, ultimately contributing to economic growth and poverty reduction. However, various factors, including gender norms, mobility, and the quality of employment, influence women's participation in the workforce. Digital technologies are rapidly transforming the workplace, impacting various sectors and creating new opportunities, while also exacerbating existing inequalities. The COVID-19 pandemic accelerated this digitalization, driving many aspects of work online, but also exposing existing digital divides along various socio-economic lines. BRICS nations, with their focus on digitalization, high populations, and significant economic contributions, provide an ideal context to examine the relationship between digitalization and FLFP. This study addresses the following questions: 1) Does digitalization enhance FLFP in BRICS nations? 2) Does education increase FLFP? 3) Does increased GDP facilitate FLFP in BRICS nations? The study employs a novel approach by analyzing the BRICS economies together and applying advanced econometric techniques.

The literature review examines prior research on the impact of digitalization, education, fertility, and economic growth on FLFP across various global contexts. Studies show mixed results regarding the influence of ICT on FLFP, with some indicating a positive association, particularly in contexts with high internet penetration and mobile phone usage, enabling greater flexibility and access to jobs. Other studies highlight the potential for ICT to exacerbate inequalities. The impact of education on FLFP is generally considered positive, empowering women and enhancing their opportunities. Conversely, high fertility rates are often negatively correlated with FLFP, due to the time constraints and childcare responsibilities associated with raising children. Economic growth's relationship with FLFP displays a more complex, often U-shaped pattern. The existing literature lacks a comprehensive study specifically focused on the interplay of these factors in the BRICS economies.

The study uses annual data from 1990 to 2020 for the five BRICS nations (Brazil, Russia, India, China, and South Africa). The theoretical model posits that FLFP is a function of digitalization, education, fertility, and GDP. To address cross-sectional dependence (CSD) in the data, the Pesaran (2015) CSD test is applied. Given CSD, third-generation unit root tests (Bai and Carrion-I-Silvestre, 2009; Pesaran, 2007) are employed to determine the order of integration of the variables. A Swamy slope homogeneity test assesses whether slope coefficients are homogeneous or heterogeneous. The Westerlund and Edgerton (2008) and Banerjee and Carrion-i-Silvestre (2017) cointegration tests examine the long-run relationship between the variables. The study employs the cross-sectionally augmented autoregressive distributed lag (CSARDL) model to estimate both short-run and long-run effects, accounting for CSD and slope heterogeneity. Robustness checks are performed using the augmented mean group (AMG) and common correlated effect mean group (CCEMG) estimators.

The empirical results reveal significant cross-sectional dependence among the variables. Unit root tests indicate that the variables are stationary at their first difference. The Swamy test confirms slope heterogeneity. Cointegration tests support a long-run relationship between FLFP and the other variables. The CSARDL model estimates reveal that digitalization has a positive and significant long-run effect on FLFP, suggesting that increased internet access promotes female labor market participation in BRICS economies. Education also displays a strong positive and significant impact on FLFP. Fertility, as anticipated, has a negative and significant long-run effect on FLFP. GDP shows a positive and statistically significant impact. Short-run results show similar patterns, but the magnitudes of the coefficients are smaller compared to the long-run effects. Robustness tests using AMG and CCEMG estimators confirm the key findings of the CSARDL model.

The findings support the hypothesis that digitalization, education, and GDP positively influence FLFP in BRICS nations. The positive relationship between digitalization and FLFP aligns with expectations that greater access to information and technology can empower women and create new employment opportunities. The significant positive effect of education underscores the importance of investing in women's education to enhance their participation in the labor force. The negative correlation between fertility and FLFP is consistent with existing literature, reflecting the time and resource constraints faced by mothers with young children. The positive correlation between GDP and FLFP is also consistent with the idea that economic growth tends to create more employment opportunities, including for women. The differences between short-run and long-run effects are consistent with the notion that the impact of these factors on female labor market participation may manifest over an extended period.

This study provides compelling evidence of the positive impact of digitalization and education on FLFP in BRICS economies. The findings highlight the importance of investments in ICT infrastructure, affordable internet access, and women's education for promoting female labor market participation. Future research could explore the role of specific policies and interventions in facilitating this relationship, examine the impact of digitalization across different sectors, and delve into regional disparities within the BRICS economies. Comparative analysis with other emerging economies would also enhance the generalizability of these findings.

While this study employs advanced econometric techniques to address potential biases, several limitations should be acknowledged. The focus is on aggregate data, masking potential heterogeneity within each country. The digitalization variable, based on internet usage, doesn't capture the nuances of digital literacy or access to specific technologies. External shocks and unobserved factors may influence the relationship between variables. Future studies employing micro-level data and exploring specific policies within the BRICS nations could address these limitations.